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metadata
license: apache-2.0
base_model:
  - mistralai/Pixtral-12B-2409
library_name: transformers

Pixtral-12B Vision Encoder

Model Overview

This repository provides direct access to the vision encoder module extracted from the Pixtral-12B multimodal model. By isolating the vision encoder, we enable researchers and developers to leverage the powerful visual feature extraction capabilities for downstream vision tasks.

Key Features

  • Standalone Vision Encoder: Extracted from the full Pixtral-12B model
  • Lightweight Architecture: Optimized 400M parameter vision encoder
  • Flexible Usage: Easily integrated into various computer vision pipelines
  • No Unnecessary Decoder Weights: Trimmed for efficient vision-specific applications

Motivation

The Pixtral-12B Vision Encoder module is designed for researchers and developers who:

  • Require high-quality visual feature extraction
  • Want to use the vision encoder independently of the full multimodal model
  • Seek to implement custom downstream vision tasks
  • Desire a lightweight, efficient vision representation module

Installation

from transformers import AutoModel
import torch

# Load the vision encoder
vision_encoder = AutoModel.from_pretrained("your-repository/pixtral-12b-vision-encoder")

Example Usage

from PIL import Image
import torch

# Load an image
image = Image.open("example_image.jpg")

# Preprocess the image (ensure to use the corresponding processor)
inputs = vision_processor(images=image, return_tensors="pt")

# Extract visual features
with torch.no_grad():
    visual_embeddings = vision_encoder(**inputs).last_hidden_state

# Now you can use visual_embeddings for downstream tasks

Capabilities

  • High-quality visual feature extraction
  • Support for various image sizes
  • Robust representation learning
  • Compatible with multiple vision downstream tasks

Limitations

  • Designed specifically for feature extraction
  • Performance may vary depending on the specific downstream task
  • Requires careful preprocessing and task-specific fine-tuning

Acknowledgements

Special thanks to the Mistral AI team for developing the original Pixtral-12B multimodal model.

License

Distributed under the Apache 2.0 License.

Citation

If you use this vision encoder in your research, please cite the original Mistral AI Pixtral-12B model.